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FMM-Net: neural network architecture based on the Fast Multipole Method
In this paper, we propose a new neural network architecture based on the H2 matrix.
Modelling hidden structure of signals in group data analysis with modified (Lr, 1) and block-term decompositions
This work is devoted to elaboration on the idea to use block term decomposition for group data analysis and to raise the possibility of modelling group activity with (Lr, 1) and Tucker blocks.
Comparative study of Discrete Wavelet Transforms and Wavelet Tensor Train decomposition to feature extraction of FTIR data of medicinal plants
Fourier-transform infra-red (FTIR) spectra of samples from 7 plant species were used to explore the influence of preprocessing and feature extraction on efficiency of machine learning algorithms.
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